A Design for Networked Flash

Size: px
Start display at page:

Download "A Design for Networked Flash"

Transcription

1 A Design for Networked Flash (Clusters Of Raw Flash Units) Mahesh Balakrishnan, John Davis, Dahlia Malkhi, Vijayan Prabhakaran, Michael Wei*, Ted Wobber Microso- Research Silicon Valley * Graduate student at UCSD

2 The I/O Story? Processors Main Memory Storage 2

3 The I/O Story Disk Capacity 1980s 30 MB Transfer Rate 1980s 2 MB/s Latency 1980s 20 ms Capacity/Bandwidth Large Transfers 1980s 15s Capacity/Bandwidth Small Transfers 1980s 600s 3

4 The I/O Story Disk Capacity s 30 MB 2 TB Transfer Rate 1980s 2 MB/s Latency 1980s 20 ms Capacity/Bandwidth Large Transfers 1980s 15s Capacity/Bandwidth Small Transfers 1980s 600s 3

5 The I/O Story Disk Capacity s 30 MB 2 TB Transfer Rate s 2 MB/s 150 MB/s Latency s 10 ms 20 ms Capacity/Bandwidth Large Transfers 1980s 15s Capacity/Bandwidth Small Transfers 1980s 600s 3

6 The I/O Story Disk Capacity s 30 MB 2 TB Transfer Rate s 2 MB/s 150 MB/s Latency s 10 ms 20 ms Capacity/Bandwidth Large Transfers s 15s 5,000s 300x Worse Capacity/Bandwidth Small Transfers 1980s 600s 3

7 The I/O Story Disk Capacity s 30 MB 2 TB Transfer Rate s 2 MB/s 150 MB/s Latency s 10 ms 20 ms Capacity/Bandwidth Large Transfers s 15s 5,000s 300x Worse Capacity/Bandwidth Small Transfers s 600s 58 days 8,000x Worse 3

8 512 Gb ~50 MB/s 1,280 4k The I/O Story 128 Mb ~50 MB/s byte 4 Mb ~200 MB/s 1 byte NAND Flash Phase Change STT- RAM 4

9 ~320GB $7,000 $21/GB 500GB- 10TB $10,000+ $20/GB 2 TB $88,000 $44/GB 5

10 PCIe 3.0 x16: 16 GB/s iscsi: 10 Gb/s SAS : 12 Gb/s ~320GB $7,000 $21/GB 500GB- 10TB $10,000+ $20/GB 2 TB $88,000 $44/GB 5

11 Ethernet PCIe 3.0 x16: 16 GB/s iscsi: 10 Gb/s SAS : 12 Gb/s ~320GB $7,000 $21/GB 500GB- 10TB $10,000+ $20/GB 2 TB $88,000 $44/GB 5

12 Ethernet Bo^leneck Single Point of Failure Difficult to Scale Power- Inefficient How fast does it need to be? PCIe 3.0 x16: 16 GB/s iscsi: 10 Gb/s SAS : 12 Gb/s ~320GB $7,000 $21/GB 500GB- 10TB $10,000+ $20/GB 2 TB $88,000 $44/GB 5

13 Outline The I/O Story CORFU Overview Hardware Plaaorm Conclusion 6

14 flash in the data center How can we leverage flash in distributed systems? Can flash clusters eliminate the trade- off between consistency and performance? What new abstracdons are required to manage and access flash clusters? 7

15 The CORFU Architecture Cluster of raw flash units 8

16 The CORFU Architecture Cluster of raw flash units 8

17 The CORFU Architecture Cluster of raw flash units No Bo^lenecks Fault Tolerant Highly Scalable Low Power (10W /unit) Cheap Cost of Flash) 8

18 what is CORFU? flash cluster 9

19 what is CORFU? read from anywhere append to tail flash cluster 9

20 what is CORFU? Replicated, fault- tolerant append read from anywhere append to tail flash cluster 9

21 what is CORFU? CORFU Replicated, fault- tolerant append read from anywhere append to tail flash cluster 9

22 what is CORFU? infrastructure applicayons: key- value stores databases SMR filesystems virtual disks CORFU Replicated, fault- tolerant append read from anywhere append to tail flash cluster 9

23 what is CORFU? infrastructure applicayons: key- value stores databases SMR filesystems virtual disks TOFU CORFU Replicated, fault- tolerant append read from anywhere append to tail flash cluster 9

24 what is CORFU? infrastructure applicayons: key- value stores databases SMR filesystems virtual disks TOFU CORFU Replicated, fault- tolerant append read from anywhere append to tail flash cluster cluster of 32 server- a^ached SSDs, 1.5 TB 0.5M reads/s, 0.2M appends/s (4KB) 9

25 what is CORFU? infrastructure applicayons: key- value stores databases SMR filesystems virtual disks TOFU CORFU Replicated, fault- tolerant append read from anywhere append to tail network- a^ached flash flash 1 cluster Gbps, 15W, 75 µs reads, 200 µs writes (4KB) cluster of 32 server- a^ached SSDs, 1.5 TB 0.5M reads/s, 0.2M appends/s (4KB) 9

26 the case for CORFU s append/read data why a shared log interface? 1.easy to build strongly consistent (transacdonal) s 2.effecdve way to pool flash: 1. SSD uses logging to avoid write- in- place 2. random reads are fast 3. GC is feasible 10

27 CORFU is a distributed SSD with a shared log interface gelng 10 Gbps random- IO from 1TB flash farm:

28 the CORFU design CORFU API: read(o) append(v) trim(o) read from anywhere append to tail 4KB log entry 12

29 the CORFU design CORFU API: read(o) append(v) trim(o) read from anywhere append to tail 4KB log entry each logical entry is mapped to a replica set of physical flash pages 12

30 the CORFU design mapping resides at the client CORFU API: read(o) append(v) trim(o) read from anywhere append to tail 4KB log entry each logical entry is mapped to a replica set of physical flash pages 12

31 the CORFU design mapping resides at the client CORFU API: read(o) append(v) trim(o) read from anywhere append to tail sequencer 4KB log entry each logical entry is mapped to a replica set of physical flash pages 12

32 the CORFU design mapping resides at the client CORFU API: read(o) CORFU append throughput: # of append(v) 64- bit tokens issued per second trim(o) read from anywhere append to tail sequencer 4KB log entry each logical entry is mapped to a replica set of physical flash pages 12

33 Striping

34 Striping

35 Striping

36 Striping

37 Striping

38 Striping

39 Striping

40 Striping

41 Striping

42 Striping

43 Chaining (Replicadon)

44 Chaining (Replicadon)

45 Chaining (Replicadon)

46 Chaining (Replicadon)

47 Chaining (Replicadon)

48 Chaining (Replicadon)

49 Chaining (Replicadon)

50 Chaining (Replicadon)

51 Chaining (Replicadon)

52 Chaining (Replicadon)

53 Chaining (Replicadon)

54 Chaining (Replicadon)

55 Chaining (Replicadon)

56 Chaining (Replicadon)

57 Chaining (Replicadon)

58 Chaining (Replicadon)

59 Chaining (Replicadon)

60 Holes

61 Holes

62 Holes

63 Holes

64 Holes

65 Holes

66 Holes

67 Holes

68 Holes

69 Holes

70 Holes

71 Holes

72 Holes

73 Holes

74 Holes X

75 Holes X

76 Holes X

77 Holes X

78 Holes X

79 Holes X

80 CORFU throughput (server+ssd) [CORFU: A Shared Log Design for Flash Clusters, NSDI 2012] 10 Gbps router X 16 servers (1 Gbps) X 2 SSDs per server Reads bounded by network bandwidth Writes are replicated, and bounded by sequencer throughput 16

81 The CORFU Hardware Append Read 17

82 The CORFU Hardware Append Read sequencer 17

83 The CORFU Hardware Append Read sequencer 17

84 The CORFU Hardware Append Read sequencer SATA Ethernet FPGA (or ASIC) NAND 17

85 The CORFU Hardware Append Read sequencer Write- Once, Address Read Trim SATA Management Ethernet FPGA (or ASIC) NAND 17

86 The CORFU Hardware Plaaorm 2 Prototype Systems XUPv5 Virtex5 XC5VLX110T 2 GB DDR2 RAM 2x SATA 2.0 BEE3 Virtex5 XC5VLX155T x4 8GB DDR2 RAM 8x SATA /64GB Flash DIMM 18

87 The CORFU Hardware Plaaorm 2 Prototype Systems XUPv5 Virtex5 XC5VLX110T 2 GB DDR2 RAM 2x SATA 2.0 BEE3 Virtex5 XC5VLX155T x4 8GB DDR2 RAM 8x SATA /64GB Flash DIMM 18

88 Hardware Design SSD DDR2 Memory SATA Core DDR2 Controller Write Core Token Ring Read Core Metadata Core Packet Processing Core FPGA prototype: 1 Gbps Ethernet Corfu protocol (UDP) SSD, not raw flash 1 Gbps PHY Ethernet Core System Core Other Cores GPIO RS232 Status

89 Our hardware

90 Our hardware Simple, low power, cheap, naturally pipelined No interrupts; no thread synchronizadon; polling throughout No data copying Can implement dme- sensidve funcdons in logic Frequency: 100 MHz

91 Our hardware Simple, low power, cheap, naturally pipelined No interrupts; no thread synchronizadon; polling throughout No data copying Can implement dme- sensidve funcdons in logic Frequency: 100 MHz power: 15W

92 Our hardware Simple, low power, cheap, naturally pipelined No interrupts; no thread synchronizadon; polling throughout No data copying Can implement dme- sensidve funcdons in logic Frequency: 100 MHz power: 15W tput: ~27,000 reads /sec (4KB) ~ 920 Mbps

93 Our hardware Simple, low power, cheap, naturally pipelined No interrupts; no thread synchronizadon; polling throughout No data copying Can implement dme- sensidve funcdons in logic Frequency: 100 MHz power: 15W tput: ~27,000 reads /sec (4KB) ~ 920 Mbps end- to- end latency (measured at NIC): reads: 75 µsecs non- mirrored appends: 200 µsecs

94 Applicadons Key- Value Store Virtual Block Device Shared Full rollback Distributed Synchronizadon (ZooKeeper)

95 Conclusion

96 Conclusion From Paxos to CORFU.. Corfu Paxos

97 Conclusion CORFU is a distributed SSD: 1 million write IOPS, linearly scalable read IOPS Corfu From Paxos to CORFU.. CORFU is a shared log: strong consistency at wire speed Paxos CORFU uses network- a^ached flash to construct inexpensive, power- efficient clusters

CORFU: A Shared Log Design for Flash Clusters

CORFU: A Shared Log Design for Flash Clusters CORFU: A Shared Log Design for Flash Clusters Authors: Mahesh Balakrishnan, Dahlia Malkhi, Vijayan Prabhakaran, Ted Wobber, Michael Wei, John D. Davis EECS 591 11/7/18 Presented by Evan Agattas and Fanzhong

More information

Differential RAID: Rethinking RAID for SSD Reliability

Differential RAID: Rethinking RAID for SSD Reliability Differential RAID: Rethinking RAID for SSD Reliability Mahesh Balakrishnan Asim Kadav 1, Vijayan Prabhakaran, Dahlia Malkhi Microsoft Research Silicon Valley 1 The University of Wisconsin-Madison Solid

More information

Memory-Based Cloud Architectures

Memory-Based Cloud Architectures Memory-Based Cloud Architectures ( Or: Technical Challenges for OnDemand Business Software) Jan Schaffner Enterprise Platform and Integration Concepts Group Example: Enterprise Benchmarking -) *%'+,#$)

More information

SSD Architecture Considerations for a Spectrum of Enterprise Applications. Alan Fitzgerald, VP and CTO SMART Modular Technologies

SSD Architecture Considerations for a Spectrum of Enterprise Applications. Alan Fitzgerald, VP and CTO SMART Modular Technologies SSD Architecture Considerations for a Spectrum of Enterprise Applications Alan Fitzgerald, VP and CTO SMART Modular Technologies Introduction Today s SSD delivers form-fit-function compatible solid-state

More information

Looking Ahead to Higher Performance SSDs with HLNAND

Looking Ahead to Higher Performance SSDs with HLNAND Looking Ahead to Higher Performance SSDs with HLNAND Roland Schuetz Director, Applications & Business Initiatives MOSAID Technologies Inc. Soogil Jeong Vice President, Engineering INDILINX Infrastructure

More information

Distributed Consensus Paxos

Distributed Consensus Paxos Distributed Consensus Paxos Ethan Cecchetti October 18, 2016 CS6410 Some structure taken from Robert Burgess s 2009 slides on this topic State Machine Replication (SMR) View a server as a state machine.

More information

NVMFS: A New File System Designed Specifically to Take Advantage of Nonvolatile Memory

NVMFS: A New File System Designed Specifically to Take Advantage of Nonvolatile Memory NVMFS: A New File System Designed Specifically to Take Advantage of Nonvolatile Memory Dhananjoy Das, Sr. Systems Architect SanDisk Corp. 1 Agenda: Applications are KING! Storage landscape (Flash / NVM)

More information

DataON and Intel Select Hyper-Converged Infrastructure (HCI) Maximizes IOPS Performance for Windows Server Software-Defined Storage

DataON and Intel Select Hyper-Converged Infrastructure (HCI) Maximizes IOPS Performance for Windows Server Software-Defined Storage Solution Brief DataON and Intel Select Hyper-Converged Infrastructure (HCI) Maximizes IOPS Performance for Windows Server Software-Defined Storage DataON Next-Generation All NVMe SSD Flash-Based Hyper-Converged

More information

Gecko: Contention-Oblivious Disk Arrays for Cloud Storage

Gecko: Contention-Oblivious Disk Arrays for Cloud Storage Gecko: Contention-Oblivious Disk Arrays for Cloud Storage Ji-Yong Shin Cornell University In collaboration with Mahesh Balakrishnan (MSR SVC), Tudor Marian (Google), and Hakim Weatherspoon (Cornell) FAST

More information

NetChain: Scale-Free Sub-RTT Coordination

NetChain: Scale-Free Sub-RTT Coordination NetChain: Scale-Free Sub-RTT Coordination Xin Jin Xiaozhou Li, Haoyu Zhang, Robert Soulé, Jeongkeun Lee, Nate Foster, Changhoon Kim, Ion Stoica Conventional wisdom: avoid coordination NetChain: lightning

More information

Extremely Fast Distributed Storage for Cloud Service Providers

Extremely Fast Distributed Storage for Cloud Service Providers Solution brief Intel Storage Builders StorPool Storage Intel SSD DC S3510 Series Intel Xeon Processor E3 and E5 Families Intel Ethernet Converged Network Adapter X710 Family Extremely Fast Distributed

More information

Moneta: A High-performance Storage Array Architecture for Nextgeneration, Micro 2010

Moneta: A High-performance Storage Array Architecture for Nextgeneration, Micro 2010 Moneta: A High-performance Storage Array Architecture for Nextgeneration, Non-volatile Memories Micro 2010 NVM-based SSD NVMs are replacing spinning-disks Performance of disks has lagged NAND flash showed

More information

I/O Acceleration by Host Side Resources

I/O Acceleration by Host Side Resources I/O Acceleration by Host Side Resources Chethan Kumar PernixData Story So Far Virtualization has resulted in Longer I/O path Through layers of storage abstraction Exponential growth in the load on the

More information

From Paxos to CORFU: A Flash-Speed Shared Log

From Paxos to CORFU: A Flash-Speed Shared Log From Paxos to CORFU: A Flash-Speed Shared Log Dahlia Malkhi dalia@microsoft.com Vijayan Prabhakaran vijayanp@microsoft.com Mahesh Balakrishnan maheshba@microsoft.com Ted Wobber wobber@microsoft.com John

More information

Authenticated Storage Using Small Trusted Hardware Hsin-Jung Yang, Victor Costan, Nickolai Zeldovich, and Srini Devadas

Authenticated Storage Using Small Trusted Hardware Hsin-Jung Yang, Victor Costan, Nickolai Zeldovich, and Srini Devadas Authenticated Storage Using Small Trusted Hardware Hsin-Jung Yang, Victor Costan, Nickolai Zeldovich, and Srini Devadas Massachusetts Institute of Technology November 8th, CCSW 2013 Cloud Storage Model

More information

Cloud Computing and Hadoop Distributed File System. UCSB CS170, Spring 2018

Cloud Computing and Hadoop Distributed File System. UCSB CS170, Spring 2018 Cloud Computing and Hadoop Distributed File System UCSB CS70, Spring 08 Cluster Computing Motivations Large-scale data processing on clusters Scan 000 TB on node @ 00 MB/s = days Scan on 000-node cluster

More information

Distributed Filesystem

Distributed Filesystem Distributed Filesystem 1 How do we get data to the workers? NAS Compute Nodes SAN 2 Distributing Code! Don t move data to workers move workers to the data! - Store data on the local disks of nodes in the

More information

Key Points. Rotational delay vs seek delay Disks are slow. Techniques for making disks faster. Flash and SSDs

Key Points. Rotational delay vs seek delay Disks are slow. Techniques for making disks faster. Flash and SSDs IO 1 Today IO 2 Key Points CPU interface and interaction with IO IO devices The basic structure of the IO system (north bridge, south bridge, etc.) The key advantages of high speed serial lines. The benefits

More information

Low-Overhead Flash Disaggregation via NVMe-over-Fabrics

Low-Overhead Flash Disaggregation via NVMe-over-Fabrics Low-Overhead Flash Disaggregation via NVMe-over-Fabrics Vijay Balakrishnan Memory Solutions Lab. Samsung Semiconductor, Inc. August 2017 1 DISCLAIMER This presentation and/or accompanying oral statements

More information

Moneta: A High-Performance Storage Architecture for Next-generation, Non-volatile Memories

Moneta: A High-Performance Storage Architecture for Next-generation, Non-volatile Memories Moneta: A High-Performance Storage Architecture for Next-generation, Non-volatile Memories Adrian M. Caulfield Arup De, Joel Coburn, Todor I. Mollov, Rajesh K. Gupta, Steven Swanson Non-Volatile Systems

More information

The Why and How of Developing All-Flash Storage Server

The Why and How of Developing All-Flash Storage Server The Why and How of Developing All-Flash Storage Server June 2016 Jungsoo Kim Manager, SK Telecom Agenda Why we care about All-Flash Storage Transforming to 5G Network Open HW & SW Projects @ SKT Our approaches

More information

Dell PowerEdge R730xd Servers with Samsung SM1715 NVMe Drives Powers the Aerospike Fraud Prevention Benchmark

Dell PowerEdge R730xd Servers with Samsung SM1715 NVMe Drives Powers the Aerospike Fraud Prevention Benchmark Dell PowerEdge R730xd Servers with Samsung SM1715 NVMe Drives Powers the Aerospike Fraud Prevention Benchmark Testing validation report prepared under contract with Dell Introduction As innovation drives

More information

CS5412: WHERE DID MY PERFORMANCE GO?

CS5412: WHERE DID MY PERFORMANCE GO? 1 CS5412: WHERE DID MY PERFORMANCE GO? Lecture XVIII Ken Birman Suppose you follow the rules 2 You set out to build a fairly complex large-scale system for some kind of important task Maybe not as mission-critical

More information

Flat Datacenter Storage. Edmund B. Nightingale, Jeremy Elson, et al. 6.S897

Flat Datacenter Storage. Edmund B. Nightingale, Jeremy Elson, et al. 6.S897 Flat Datacenter Storage Edmund B. Nightingale, Jeremy Elson, et al. 6.S897 Motivation Imagine a world with flat data storage Simple, Centralized, and easy to program Unfortunately, datacenter networks

More information

RDMA and Hardware Support

RDMA and Hardware Support RDMA and Hardware Support SIGCOMM Topic Preview 2018 Yibo Zhu Microsoft Research 1 The (Traditional) Journey of Data How app developers see the network Under the hood This architecture had been working

More information

Feedback on BeeGFS. A Parallel File System for High Performance Computing

Feedback on BeeGFS. A Parallel File System for High Performance Computing Feedback on BeeGFS A Parallel File System for High Performance Computing Philippe Dos Santos et Georges Raseev FR 2764 Fédération de Recherche LUmière MATière December 13 2016 LOGO CNRS LOGO IO December

More information

Willow: A User- Programmable SSD

Willow: A User- Programmable SSD Willow: A User- Programmable SSD Sudharsan Seshadri, Mark Gahagan, Sundaram Bhaskaran, Trevor Bunker, Arup De, Yanqin Jin, Yang Liu, and Steven Swanson Non- VolaDle Systems Laboratory Computer Science

More information

Multimedia Streaming. Mike Zink

Multimedia Streaming. Mike Zink Multimedia Streaming Mike Zink Technical Challenges Servers (and proxy caches) storage continuous media streams, e.g.: 4000 movies * 90 minutes * 10 Mbps (DVD) = 27.0 TB 15 Mbps = 40.5 TB 36 Mbps (BluRay)=

More information

Warehouse- Scale Computing and the BDAS Stack

Warehouse- Scale Computing and the BDAS Stack Warehouse- Scale Computing and the BDAS Stack Ion Stoica UC Berkeley UC BERKELEY Overview Workloads Hardware trends and implications in modern datacenters BDAS stack What is Big Data used For? Reports,

More information

Low-Overhead Flash Disaggregation via NVMe-over-Fabrics Vijay Balakrishnan Memory Solutions Lab. Samsung Semiconductor, Inc.

Low-Overhead Flash Disaggregation via NVMe-over-Fabrics Vijay Balakrishnan Memory Solutions Lab. Samsung Semiconductor, Inc. Low-Overhead Flash Disaggregation via NVMe-over-Fabrics Vijay Balakrishnan Memory Solutions Lab. Samsung Semiconductor, Inc. 1 DISCLAIMER This presentation and/or accompanying oral statements by Samsung

More information

UCS Invicta: A New Generation of Storage Performance. Mazen Abou Najm DC Consulting Systems Engineer

UCS Invicta: A New Generation of Storage Performance. Mazen Abou Najm DC Consulting Systems Engineer UCS Invicta: A New Generation of Storage Performance Mazen Abou Najm DC Consulting Systems Engineer HDDs Aren t Designed For High Performance Disk 101 Can t spin faster (200 IOPS/Drive) Can t seek faster

More information

COMP283-Lecture 3 Applied Database Management

COMP283-Lecture 3 Applied Database Management COMP283-Lecture 3 Applied Database Management Introduction DB Design Continued Disk Sizing Disk Types & Controllers DB Capacity 1 COMP283-Lecture 3 DB Storage: Linear Growth Disk space requirements increases

More information

SOFTWARE-DEFINED BLOCK STORAGE FOR HYPERSCALE APPLICATIONS

SOFTWARE-DEFINED BLOCK STORAGE FOR HYPERSCALE APPLICATIONS SOFTWARE-DEFINED BLOCK STORAGE FOR HYPERSCALE APPLICATIONS SCALE-OUT SERVER SAN WITH DISTRIBUTED NVME, POWERED BY HIGH-PERFORMANCE NETWORK TECHNOLOGY INTRODUCTION The evolution in data-centric applications,

More information

Isilon Performance. Name

Isilon Performance. Name 1 Isilon Performance Name 2 Agenda Architecture Overview Next Generation Hardware Performance Caching Performance Streaming Reads Performance Tuning OneFS Architecture Overview Copyright 2014 EMC Corporation.

More information

Highly Scalable, Non-RDMA NVMe Fabric. Bob Hansen,, VP System Architecture

Highly Scalable, Non-RDMA NVMe Fabric. Bob Hansen,, VP System Architecture A Cost Effective,, High g Performance,, Highly Scalable, Non-RDMA NVMe Fabric Bob Hansen,, VP System Architecture bob@apeirondata.com Storage Developers Conference, September 2015 Agenda 3 rd Platform

More information

No More Waiting Around

No More Waiting Around White Paper 10 GbE NETWORK UPGRADE FOR SMB FOR IT ADMINISTRATORS, DECISION-MAKERS, AND OWNERS OF SMALL TO MEDIUM-SIZED BUSINESSES No More Waiting Around How 10 Gb/s Will Change Your Company Network Introduction

More information

Data Processing at the Speed of 100 Gbps using Apache Crail. Patrick Stuedi IBM Research

Data Processing at the Speed of 100 Gbps using Apache Crail. Patrick Stuedi IBM Research Data Processing at the Speed of 100 Gbps using Apache Crail Patrick Stuedi IBM Research The CRAIL Project: Overview Data Processing Framework (e.g., Spark, TensorFlow, λ Compute) Spark-IO FS Albis Streaming

More information

Be Fast, Cheap and in Control with SwitchKV Xiaozhou Li

Be Fast, Cheap and in Control with SwitchKV Xiaozhou Li Be Fast, Cheap and in Control with SwitchKV Xiaozhou Li Raghav Sethi Michael Kaminsky David G. Andersen Michael J. Freedman Goal: fast and cost-effective key-value store Target: cluster-level storage for

More information

Storage. CS 3410 Computer System Organization & Programming

Storage. CS 3410 Computer System Organization & Programming Storage CS 3410 Computer System Organization & Programming These slides are the product of many rounds of teaching CS 3410 by Deniz Altinbuke, Kevin Walsh, and Professors Weatherspoon, Bala, Bracy, and

More information

Managing Array of SSDs When the Storage Device is No Longer the Performance Bottleneck

Managing Array of SSDs When the Storage Device is No Longer the Performance Bottleneck Managing Array of Ds When the torage Device is No Longer the Performance Bottleneck Byung. Kim, Jaeho Kim, am H. Noh UNIT (Ulsan National Institute of cience & Technology) Outline Motivation & Observation

More information

Ambry: LinkedIn s Scalable Geo- Distributed Object Store

Ambry: LinkedIn s Scalable Geo- Distributed Object Store Ambry: LinkedIn s Scalable Geo- Distributed Object Store Shadi A. Noghabi *, Sriram Subramanian +, Priyesh Narayanan +, Sivabalan Narayanan +, Gopalakrishna Holla +, Mammad Zadeh +, Tianwei Li +, Indranil

More information

Accelerating Real-Time Big Data. Breaking the limitations of captive NVMe storage

Accelerating Real-Time Big Data. Breaking the limitations of captive NVMe storage Accelerating Real-Time Big Data Breaking the limitations of captive NVMe storage 18M IOPs in 2u Agenda Everything related to storage is changing! The 3rd Platform NVM Express architected for solid state

More information

CSE 124: Networked Services Lecture-16

CSE 124: Networked Services Lecture-16 Fall 2010 CSE 124: Networked Services Lecture-16 Instructor: B. S. Manoj, Ph.D http://cseweb.ucsd.edu/classes/fa10/cse124 11/23/2010 CSE 124 Networked Services Fall 2010 1 Updates PlanetLab experiments

More information

Flash Trends: Challenges and Future

Flash Trends: Challenges and Future Flash Trends: Challenges and Future John D. Davis work done at Microsoft Researcher- Silicon Valley in collaboration with Laura Caulfield*, Steve Swanson*, UCSD* 1 My Research Areas of Interest Flash characteristics

More information

All-Flash Storage System

All-Flash Storage System All-Flash Storage System June 2016 Jungsoo Kim Manager, SK Telecom Agenda SKT Storage Solution R&D Introduction Our approaches in developing storage system AF-Media details Computing Board Storage Module

More information

Flash Controller Solutions in Programmable Technology

Flash Controller Solutions in Programmable Technology Flash Controller Solutions in Programmable Technology David McIntyre Senior Business Unit Manager Computer and Storage Business Unit Altera Corp. dmcintyr@altera.com Flash Memory Summit 2012 Santa Clara,

More information

Data Processing at the Speed of 100 Gbps using Apache Crail. Patrick Stuedi IBM Research

Data Processing at the Speed of 100 Gbps using Apache Crail. Patrick Stuedi IBM Research Data Processing at the Speed of 100 Gbps using Apache Crail Patrick Stuedi IBM Research The CRAIL Project: Overview Data Processing Framework (e.g., Spark, TensorFlow, λ Compute) Spark-IO Albis Pocket

More information

NVMe Direct. Next-Generation Offload Technology. White Paper

NVMe Direct. Next-Generation Offload Technology. White Paper NVMe Direct Next-Generation Offload Technology The market introduction of high-speed NVMe SSDs and 25/40/50/100Gb Ethernet creates exciting new opportunities for external storage NVMe Direct enables high-performance

More information

The Google File System

The Google File System The Google File System Sanjay Ghemawat, Howard Gobioff and Shun Tak Leung Google* Shivesh Kumar Sharma fl4164@wayne.edu Fall 2015 004395771 Overview Google file system is a scalable distributed file system

More information

NEC M100 Frequently Asked Questions September, 2011

NEC M100 Frequently Asked Questions September, 2011 What RAID levels are supported in the M100? 1,5,6,10,50,60,Triple Mirror What is the power consumption of M100 vs. D4? The M100 consumes 26% less energy. The D4-30 Base Unit (w/ 3.5" SAS15K x 12) consumes

More information

Storage Systems : Disks and SSDs. Manu Awasthi CASS 2018

Storage Systems : Disks and SSDs. Manu Awasthi CASS 2018 Storage Systems : Disks and SSDs Manu Awasthi CASS 2018 Why study storage? Scalable High Performance Main Memory System Using Phase-Change Memory Technology, Qureshi et al, ISCA 2009 Trends Total amount

More information

CSE 124: Networked Services Fall 2009 Lecture-19

CSE 124: Networked Services Fall 2009 Lecture-19 CSE 124: Networked Services Fall 2009 Lecture-19 Instructor: B. S. Manoj, Ph.D http://cseweb.ucsd.edu/classes/fa09/cse124 Some of these slides are adapted from various sources/individuals including but

More information

VMware Virtual SAN. Technical Walkthrough. Massimiliano Moschini Brand Specialist VCI - vexpert VMware Inc. All rights reserved.

VMware Virtual SAN. Technical Walkthrough. Massimiliano Moschini Brand Specialist VCI - vexpert VMware Inc. All rights reserved. VMware Virtual SAN Technical Walkthrough Massimiliano Moschini Brand Specialist VCI - vexpert 2014 VMware Inc. All rights reserved. VMware Storage Innovations VI 3.x VMFS Snapshots Storage vmotion NAS

More information

Be Fast, Cheap and in Control with SwitchKV. Xiaozhou Li

Be Fast, Cheap and in Control with SwitchKV. Xiaozhou Li Be Fast, Cheap and in Control with SwitchKV Xiaozhou Li Goal: fast and cost-efficient key-value store Store, retrieve, manage key-value objects Get(key)/Put(key,value)/Delete(key) Target: cluster-level

More information

Cluster Setup and Distributed File System

Cluster Setup and Distributed File System Cluster Setup and Distributed File System R&D Storage for the R&D Storage Group People Involved Gaetano Capasso - INFN-Naples Domenico Del Prete INFN-Naples Diacono Domenico INFN-Bari Donvito Giacinto

More information

Copyright 2012 EMC Corporation. All rights reserved.

Copyright 2012 EMC Corporation. All rights reserved. 1 2 Flash.Next: Zero To One Million IOPs Karthik Pinnamaneni Sr. Systems Engineer Karthik.Pinnamaneni@emc.com 3 An Order Of Magnitude Better Performance 2000 IOPS/GB 0.5 IOPS/GB 150 IOPS/GB 4000X FASTER

More information

Flashed-Optimized VPSA. Always Aligned with your Changing World

Flashed-Optimized VPSA. Always Aligned with your Changing World Flashed-Optimized VPSA Always Aligned with your Changing World Yair Hershko Co-founder, VP Engineering, Zadara Storage 3 Modern Data Storage for Modern Computing Innovating data services to meet modern

More information

Scaling Internet TV Content Delivery ALEX GUTARIN DIRECTOR OF ENGINEERING, NETFLIX

Scaling Internet TV Content Delivery ALEX GUTARIN DIRECTOR OF ENGINEERING, NETFLIX Scaling Internet TV Content Delivery ALEX GUTARIN DIRECTOR OF ENGINEERING, NETFLIX Inventing Internet TV Available in more than 190 countries 104+ million subscribers Lots of Streaming == Lots of Traffic

More information

Deploy a High-Performance Database Solution: Cisco UCS B420 M4 Blade Server with Fusion iomemory PX600 Using Oracle Database 12c

Deploy a High-Performance Database Solution: Cisco UCS B420 M4 Blade Server with Fusion iomemory PX600 Using Oracle Database 12c White Paper Deploy a High-Performance Database Solution: Cisco UCS B420 M4 Blade Server with Fusion iomemory PX600 Using Oracle Database 12c What You Will Learn This document demonstrates the benefits

More information

Data Management. Parallel Filesystems. Dr David Henty HPC Training and Support

Data Management. Parallel Filesystems. Dr David Henty HPC Training and Support Data Management Dr David Henty HPC Training and Support d.henty@epcc.ed.ac.uk +44 131 650 5960 Overview Lecture will cover Why is IO difficult Why is parallel IO even worse Lustre GPFS Performance on ARCHER

More information

Assessing performance in HP LeftHand SANs

Assessing performance in HP LeftHand SANs Assessing performance in HP LeftHand SANs HP LeftHand Starter, Virtualization, and Multi-Site SANs deliver reliable, scalable, and predictable performance White paper Introduction... 2 The advantages of

More information

Distributed Systems 16. Distributed File Systems II

Distributed Systems 16. Distributed File Systems II Distributed Systems 16. Distributed File Systems II Paul Krzyzanowski pxk@cs.rutgers.edu 1 Review NFS RPC-based access AFS Long-term caching CODA Read/write replication & disconnected operation DFS AFS

More information

Cloudian Sizing and Architecture Guidelines

Cloudian Sizing and Architecture Guidelines Cloudian Sizing and Architecture Guidelines The purpose of this document is to detail the key design parameters that should be considered when designing a Cloudian HyperStore architecture. The primary

More information

Solid State Storage Technologies. Jin-Soo Kim Computer Systems Laboratory Sungkyunkwan University

Solid State Storage Technologies. Jin-Soo Kim Computer Systems Laboratory Sungkyunkwan University Solid State Storage Technologies Jin-Soo Kim (jinsookim@skku.edu) Computer Systems Laboratory Sungkyunkwan University http://csl.skku.edu NVMe (1) The industry standard interface for high-performance NVM

More information

Authors : Sanjay Ghemawat, Howard Gobioff, Shun-Tak Leung Presentation by: Vijay Kumar Chalasani

Authors : Sanjay Ghemawat, Howard Gobioff, Shun-Tak Leung Presentation by: Vijay Kumar Chalasani The Authors : Sanjay Ghemawat, Howard Gobioff, Shun-Tak Leung Presentation by: Vijay Kumar Chalasani CS5204 Operating Systems 1 Introduction GFS is a scalable distributed file system for large data intensive

More information

FlashGrid Software Enables Converged and Hyper-Converged Appliances for Oracle* RAC

FlashGrid Software Enables Converged and Hyper-Converged Appliances for Oracle* RAC white paper FlashGrid Software Intel SSD DC P3700/P3600/P3500 Topic: Hyper-converged Database/Storage FlashGrid Software Enables Converged and Hyper-Converged Appliances for Oracle* RAC Abstract FlashGrid

More information

Application Acceleration Beyond Flash Storage

Application Acceleration Beyond Flash Storage Application Acceleration Beyond Flash Storage Session 303C Mellanox Technologies Flash Memory Summit July 2014 Accelerating Applications, Step-by-Step First Steps Make compute fast Moore s Law Make storage

More information

An Intelligent NIC Design Xin Song

An Intelligent NIC Design Xin Song 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) An Intelligent NIC Design Xin Song School of Electronic and Information Engineering Tianjin Vocational

More information

A Next Generation Home Access Point and Router

A Next Generation Home Access Point and Router A Next Generation Home Access Point and Router Product Marketing Manager Network Communication Technology and Application of the New Generation Points of Discussion Why Do We Need a Next Gen Home Router?

More information

vsan Stretched Cluster Bandwidth Sizing First Published On: Last Updated On:

vsan Stretched Cluster Bandwidth Sizing First Published On: Last Updated On: vsan Stretched Cluster Bandwidth Sizing First Published On: 07-20-2016 Last Updated On: 11-22-2017 1 Table of Contents 1. VSAN Stretched Cluster 1.1.Overview 1.2.General Guidelines 1.3.Bandwidth Requirements

More information

The Google File System

The Google File System The Google File System Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung December 2003 ACM symposium on Operating systems principles Publisher: ACM Nov. 26, 2008 OUTLINE INTRODUCTION DESIGN OVERVIEW

More information

Cluster-Level Google How we use Colossus to improve storage efficiency

Cluster-Level Google How we use Colossus to improve storage efficiency Cluster-Level Storage @ Google How we use Colossus to improve storage efficiency Denis Serenyi Senior Staff Software Engineer dserenyi@google.com November 13, 2017 Keynote at the 2nd Joint International

More information

NVMe Takes It All, SCSI Has To Fall. Brave New Storage World. Lugano April Alexander Ruebensaal

NVMe Takes It All, SCSI Has To Fall. Brave New Storage World. Lugano April Alexander Ruebensaal Lugano April 2018 NVMe Takes It All, SCSI Has To Fall freely adapted from ABBA Brave New Storage World Alexander Ruebensaal 1 Design, Implementation, Support & Operating of optimized IT Infrastructures

More information

IBM V7000 Unified R1.4.2 Asynchronous Replication Performance Reference Guide

IBM V7000 Unified R1.4.2 Asynchronous Replication Performance Reference Guide V7 Unified Asynchronous Replication Performance Reference Guide IBM V7 Unified R1.4.2 Asynchronous Replication Performance Reference Guide Document Version 1. SONAS / V7 Unified Asynchronous Replication

More information

Computer Architecture 计算机体系结构. Lecture 6. Data Storage and I/O 第六讲 数据存储和输入输出. Chao Li, PhD. 李超博士

Computer Architecture 计算机体系结构. Lecture 6. Data Storage and I/O 第六讲 数据存储和输入输出. Chao Li, PhD. 李超博士 Computer Architecture 计算机体系结构 Lecture 6. Data Storage and I/O 第六讲 数据存储和输入输出 Chao Li, PhD. 李超博士 SJTU-SE346, Spring 2018 Review Memory hierarchy Cache and virtual memory Locality principle Miss cache, victim

More information

Google File System. Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Google fall DIP Heerak lim, Donghun Koo

Google File System. Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Google fall DIP Heerak lim, Donghun Koo Google File System Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Google 2017 fall DIP Heerak lim, Donghun Koo 1 Agenda Introduction Design overview Systems interactions Master operation Fault tolerance

More information

Ceph in a Flash. Micron s Adventures in All-Flash Ceph Storage. Ryan Meredith & Brad Spiers, Micron Principal Solutions Engineer and Architect

Ceph in a Flash. Micron s Adventures in All-Flash Ceph Storage. Ryan Meredith & Brad Spiers, Micron Principal Solutions Engineer and Architect Ceph in a Flash Micron s Adventures in All-Flash Ceph Storage Ryan Meredith & Brad Spiers, Micron Principal Solutions Engineer and Architect 217 Micron Technology, Inc. All rights reserved. Information,

More information

Pivot3 Acuity with Microsoft SQL Server Reference Architecture

Pivot3 Acuity with Microsoft SQL Server Reference Architecture Pivot3 Acuity with Microsoft SQL Server 2014 Reference Architecture How to Contact Pivot3 Pivot3, Inc. General Information: info@pivot3.com 221 West 6 th St., Suite 750 Sales: sales@pivot3.com Austin,

More information

From Rack Scale to Network Scale: NVMe Over Fabrics Enables Exabyte Applica>ons. Zivan Ori, CEO & Co-founder, E8 Storage

From Rack Scale to Network Scale: NVMe Over Fabrics Enables Exabyte Applica>ons. Zivan Ori, CEO & Co-founder, E8 Storage From Rack Scale to Network Scale: NVMe Over Fabrics Enables Exabyte Applica>ons Zivan Ori, CEO & Co-founder, E8 Storage NVMe Over Fabrics Who? Why? How? Who is using NVMe over fabrics? Why do they need

More information

Architecting a High Performance Storage System

Architecting a High Performance Storage System WHITE PAPER Intel Enterprise Edition for Lustre* Software High Performance Data Division Architecting a High Performance Storage System January 2014 Contents Introduction... 1 A Systematic Approach to

More information

Dynamically Scalable, Fault-Tolerant Coordination on a Shared Logging Service

Dynamically Scalable, Fault-Tolerant Coordination on a Shared Logging Service Dynamically Scalable, Fault-Tolerant Coordination on a Shared Logging Service Michael Wei,, Mahesh Balakrishnan, John D. Davis, Dahlia Malkhi, Vijayan Prabhakaran and Ted Wobber University of California,

More information

DDN. DDN Updates. Data DirectNeworks Japan, Inc Shuichi Ihara. DDN Storage 2017 DDN Storage

DDN. DDN Updates. Data DirectNeworks Japan, Inc Shuichi Ihara. DDN Storage 2017 DDN Storage DDN DDN Updates Data DirectNeworks Japan, Inc Shuichi Ihara DDN A Broad Range of Technologies to Best Address Your Needs Protection Security Data Distribution and Lifecycle Management Open Monitoring Your

More information

CS60021: Scalable Data Mining. Sourangshu Bhattacharya

CS60021: Scalable Data Mining. Sourangshu Bhattacharya CS60021: Scalable Data Mining Sourangshu Bhattacharya In this Lecture: Outline: HDFS Motivation HDFS User commands HDFS System architecture HDFS Implementation details Sourangshu Bhattacharya Computer

More information

HADP Talk BlueDBM: An appliance for Big Data Analytics

HADP Talk BlueDBM: An appliance for Big Data Analytics HADP Talk BlueDBM: An appliance for Big Data Analytics Sang-Woo Jun* Ming Liu* Sungjin Lee* Jamey Hicks+ John Ankcorn+ Myron King+ Shuotao Xu* Arvind* *MIT Computer Science and Artificial Intelligence

More information

DeclStore: Layering is for the Faint of Heart

DeclStore: Layering is for the Faint of Heart DeclStore: Layering is for the Faint of Heart [HotStorage, July 2017] Noah Watkins, Michael Sevilla, Ivo Jimenez, Kathryn Dahlgren, Peter Alvaro, Shel Finkelstein, Carlos Maltzahn Layers on layers on layers

More information

Identifying Performance Bottlenecks with Real- World Applications and Flash-Based Storage

Identifying Performance Bottlenecks with Real- World Applications and Flash-Based Storage Identifying Performance Bottlenecks with Real- World Applications and Flash-Based Storage TechTarget Dennis Martin 1 Agenda About Demartek Enterprise Data Center Environments Storage Performance Metrics

More information

ZHT: Const Eventual Consistency Support For ZHT. Group Member: Shukun Xie Ran Xin

ZHT: Const Eventual Consistency Support For ZHT. Group Member: Shukun Xie Ran Xin ZHT: Const Eventual Consistency Support For ZHT Group Member: Shukun Xie Ran Xin Outline Problem Description Project Overview Solution Maintains Replica List for Each Server Operation without Primary Server

More information

No compromises: distributed transac2ons with consistency, availability, and performance

No compromises: distributed transac2ons with consistency, availability, and performance No compromises: distributed transac2ons with consistency, availability, and performance Aleksandar Dragojevic, Dushyanth Narayanan, Edmund B. Nigh2ngale, MaDhew Renzelmann, Alex Shamis, Anirudh Badam,

More information

Certification Document GRAFENTHAL GmbH R2208 S2 01/04/2016. GRAFENTHAL GmbH R2208 S2 Storage system

Certification Document GRAFENTHAL GmbH R2208 S2 01/04/2016. GRAFENTHAL GmbH R2208 S2 Storage system GRAFENTHAL GmbH R2208 S2 Storage system Executive summary After performing all tests, the GRAFENTHAL GmbH R2208 S2 has been officially certified according to the Open-E Hardware Certification Program Guide

More information

Software Defined Storage at the Speed of Flash. PRESENTATION TITLE GOES HERE Carlos Carrero Rajagopal Vaideeswaran Symantec

Software Defined Storage at the Speed of Flash. PRESENTATION TITLE GOES HERE Carlos Carrero Rajagopal Vaideeswaran Symantec Software Defined Storage at the Speed of Flash PRESENTATION TITLE GOES HERE Carlos Carrero Rajagopal Vaideeswaran Symantec Agenda Introduction Software Technology Architecture Review Oracle Configuration

More information

Google File System. By Dinesh Amatya

Google File System. By Dinesh Amatya Google File System By Dinesh Amatya Google File System (GFS) Sanjay Ghemawat, Howard Gobioff, Shun-Tak Leung designed and implemented to meet rapidly growing demand of Google's data processing need a scalable

More information

M7: Next Generation SPARC. Hotchips 26 August 12, Stephen Phillips Senior Director, SPARC Architecture Oracle

M7: Next Generation SPARC. Hotchips 26 August 12, Stephen Phillips Senior Director, SPARC Architecture Oracle M7: Next Generation SPARC Hotchips 26 August 12, 2014 Stephen Phillips Senior Director, SPARC Architecture Oracle Safe Harbor Statement The following is intended to outline our general product direction.

More information

RapidIO.org Update. Mar RapidIO.org 1

RapidIO.org Update. Mar RapidIO.org 1 RapidIO.org Update rickoco@rapidio.org Mar 2015 2015 RapidIO.org 1 Outline RapidIO Overview & Markets Data Center & HPC Communications Infrastructure Industrial Automation Military & Aerospace RapidIO.org

More information

HPC File Systems and Storage. Irena Johnson University of Notre Dame Center for Research Computing

HPC File Systems and Storage. Irena Johnson University of Notre Dame Center for Research Computing HPC File Systems and Storage Irena Johnson University of Notre Dame Center for Research Computing HPC (High Performance Computing) Aggregating computer power for higher performance than that of a typical

More information

The Google File System (GFS)

The Google File System (GFS) 1 The Google File System (GFS) CS60002: Distributed Systems Antonio Bruto da Costa Ph.D. Student, Formal Methods Lab, Dept. of Computer Sc. & Engg., Indian Institute of Technology Kharagpur 2 Design constraints

More information

Improving DPDK Performance

Improving DPDK Performance Improving DPDK Performance Data Plane Development Kit (DPDK) was pioneered by Intel as a way to boost the speed of packet API with standard hardware. DPDK-enabled applications typically show four or more

More information

Dell Reference Configuration for Large Oracle Database Deployments on Dell EqualLogic Storage

Dell Reference Configuration for Large Oracle Database Deployments on Dell EqualLogic Storage Dell Reference Configuration for Large Oracle Database Deployments on Dell EqualLogic Storage Database Solutions Engineering By Raghunatha M, Ravi Ramappa Dell Product Group October 2009 Executive Summary

More information

Cisco UCS C240 M4 I/O Characterization

Cisco UCS C240 M4 I/O Characterization White Paper Cisco UCS C240 M4 I/O Characterization Executive Summary This document outlines the I/O performance characteristics of the Cisco UCS C240 M4 Rack Server using the Cisco 12-Gbps SAS modular

More information

OpenIO SDS on ARM A practical and cost-effective object storage infrastructure based on SoYouStart dedicated ARM servers.

OpenIO SDS on ARM A practical and cost-effective object storage infrastructure based on SoYouStart dedicated ARM servers. OpenIO SDS on ARM A practical and cost-effective object storage infrastructure based on SoYouStart dedicated ARM servers. Copyright 217 OpenIO SAS All Rights Reserved. Restriction on Disclosure and Use

More information

Opportunities from our Compute, Network, and Storage Inflection Points

Opportunities from our Compute, Network, and Storage Inflection Points Opportunities from our Compute, Network, and Storage Inflection Points The Brave New Persistent World Rob Peglar Senior VP & CTO Symbolic IO Santa Clara, CA August 2016 1 Wisdom The Macro Trend Back to

More information